SRTM, which flew in 2000 on the Space Shuttle, acquired the only global-scale spaceborne single-pass INSAR data set in existence. To date, the full InSAR observation from SRTM, the coherence and phase from multiple baselines and multiple polarizations, has never been exploited, except during the production of the near global DEM using the amalgamated phase. For every location on earth between ± 60 degrees, SRTM acquired crossing paths of InSAR HH/VV data, with incidence angles between 20 and 60 degrees. This data set therefore forms a multi-baseline polarimetric data set at each imaged ground location.
It is critical that NASA understand the implications of single-pass InSAR missions (such as resolution, accuracy, coverage, and biases) such as the DLR Tandem-X and the Tandem-L mission concept in the context of the DESDynI mission. The SRTM correlation data will provide a continental scale prototype data set for vegetation height estimation. We will use Lidar data to produce a model of the vegetation structure used in the estimation of forest height.
First, we will remove and calibrate systematic SRTM errors, and make this corrected product available for community use. Second, we will demonstrate vegetation height and moment estimation over 4 diverse vegetation sites (tropical and temperate forest sites with existing Lidar data), thereby enabling global map production. Third, we will produce regional InSAR-derived vegetation structure estimates. Fourth, we will incorporate regional vegetation structure estimates into the NASA-CASA ecosystem carbon model, and measure the improvement in predictions of standing forest biomass.
Three products will be produced and made available (through an existing NASA Measures task) to the research community: a corrected correlation product, a vegetation height product, and a standing forest biomass product, for all of North and South America covered by SRTM.